TapFix: Cursorless Typographical Error Correction for Touch-Sensor Displays

We present TapFix, a cursorless mobile text correction method for touch-sensor displays. Unlike traditional methods, TapFix eliminates the need to position a cursor to make corrections. Instead, the method allows for direct, character-level access, offering easy-to-use swipe gestures on a zoomed-in target word for corrective actions. A user study with 15 participants compared TapFix to two traditional text correction methods on Apple iOS. For each of the three methods, participants completed 100 text correction tasks of four different error types on an Apple iPhone 14 Pro. The TapFix method was on average between 43.0% and 44.1% faster than the existing methods in completing the tasks. Participants also reported experiencing 5.6% to 21.1% lower levels of frustration with TapFix, as indicated by post-experiment NASA TLX and SUS questionnaires, compared to the traditional methods. Additionally, they attributed a level of usability to TapFix that was comparable to the well-established TextMagnifier method.

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Publication Details

Journal
Sensors
Published
2025-02-26
DOI
https://doi.org/10.3390/s25051421
Citations
1
Primary Topic
Interactive and Immersive Displays
Type
article
Field-Weighted Citation Impact
0.00

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article

TapFix: Cursorless Typographical Error Correction for Touch-Sensor Displays

Ian Scott MacKenzie, Aijun An, Nicholas Dehnen
1 citations
Sensors
Interactive and Immersive Displays
article

TapFix: Cursorless Typographical Error Correction for Touch-Sensor Displays

Ian Scott MacKenzie, Aijun An, Nicholas Dehnen
article en
1 citations

Abstract

We present TapFix, a cursorless mobile text correction method for touch-sensor displays. Unlike traditional methods, TapFix eliminates the need to position a cursor to make corrections. Instead, the method allows for direct, character-level access, offering easy-to-use swipe gestures on a zoomed-in target word for corrective actions. A user study with 15 participants compared TapFix to two traditional text correction methods on Apple iOS. For each of the three methods, participants completed 100 text correction tasks of four different error types on an Apple iPhone 14 Pro. The TapFix method was on average between 43.0% and 44.1% faster than the existing methods in completing the tasks. Participants also reported experiencing 5.6% to 21.1% lower levels of frustration with TapFix, as indicated by post-experiment NASA TLX and SUS questionnaires, compared to the traditional methods. Additionally, they attributed a level of usability to TapFix that was comparable to the well-established TextMagnifier method.

SensorsVol. 25(5)
York University (CA)
Natural Sciences and Engineering Research Council of Canada
Quality Education
Openalex Percentile: Top 98%
Interactive and Immersive Displays
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